Παρακολούθηση
Taiji Suzuki
Taiji Suzuki
The University of Tokyo
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα mist.i.u-tokyo.ac.jp - Αρχική σελίδα
Τίτλος
Παρατίθεται από
Παρατίθεται από
Έτος
Density ratio estimation in machine learning
M Sugiyama, T Suzuki, T Kanamori
Cambridge University Press, 2012
7382012
Direct importance estimation for covariate shift adaptation
M Sugiyama, T Suzuki, S Nakajima, H Kashima, P Von Bünau, ...
Annals of the Institute of Statistical Mathematics 60, 699-746, 2008
5332008
Graph neural networks exponentially lose expressive power for node classification
K Oono, T Suzuki
arXiv preprint arXiv:1905.10947, 2019
3682019
Adaptivity of deep ReLU network for learning in Besov and mixed smooth Besov spaces: optimal rate and curse of dimensionality
T Suzuki
International Conference on Learning Representations, 2019
2872019
Density-ratio matching under the bregman divergence: a unified framework of density-ratio estimation
M Sugiyama, T Suzuki, T Kanamori
Annals of the Institute of Statistical Mathematics 64, 1009-1044, 2012
2332012
Statistical performance of convex tensor decomposition
R Tomioka, T Suzuki, K Hayashi, H Kashima
Advances in neural information processing systems 24, 2011
1912011
Dual averaging and proximal gradient descent for online alternating direction multiplier method
T Suzuki
International Conference on Machine Learning, 392-400, 2013
1842013
Convex tensor decomposition via structured schatten norm regularization
R Tomioka, T Suzuki
Advances in neural information processing systems 26, 2013
1702013
Approximating mutual information by maximum likelihood density ratio estimation
T Suzuki, M Sugiyama, J Sese, T Kanamori
New challenges for feature selection in data mining and knowledge discovery …, 2008
1682008
High-dimensional asymptotics of feature learning: How one gradient step improves the representation
J Ba, MA Erdogdu, T Suzuki, Z Wang, D Wu, G Yang
Advances in Neural Information Processing Systems 35, 37932-37946, 2022
1642022
Relative density-ratio estimation for robust distribution comparison
M Yamada, T Suzuki, T Kanamori, H Hachiya, M Sugiyama
Neural computation 25 (5), 1324-1370, 2013
1592013
Mutual information estimation reveals global associations between stimuli and biological processes
T Suzuki, M Sugiyama, T Kanamori, J Sese
BMC bioinformatics 10, 1-12, 2009
1512009
Statistical analysis of kernel-based least-squares density-ratio estimation
T Kanamori, T Suzuki, M Sugiyama
Machine Learning 86, 335-367, 2012
1302012
Relative density-ratio estimation for robust distribution comparison
M Yamada, T Suzuki, T Kanamori, H Hachiya, M Sugiyama
Advances in neural information processing systems 24, 2011
1212011
Super-Linear Convergence of Dual Augmented Lagrangian Algorithm for Sparsity Regularized Estimation.
R Tomioka, T Suzuki, M Sugiyama
Journal of Machine Learning Research 12 (5), 2011
1132011
Diffusion models are minimax optimal distribution estimators
K Oko, S Akiyama, T Suzuki
International Conference on Machine Learning, 26517-26582, 2023
1072023
Least-squares conditional density estimation
M Sugiyama, I Takeuchi, T Suzuki, T Kanamori, H Hachiya, D Okanohara
IEICE Transactions on Information and Systems 93 (3), 583-594, 2010
962010
Generalization of two-layer neural networks: An asymptotic viewpoint
J Ba, M Erdogdu, T Suzuki, D Wu, T Zhang
International conference on learning representations, 2020
932020
Cross-domain recommendation via deep domain adaptation
H Kanagawa, H Kobayashi, N Shimizu, Y Tagami, T Suzuki
European Conference on Information Retrieval, 20-29, 2019
902019
Stochastic particle gradient descent for infinite ensembles
A Nitanda, T Suzuki
arXiv preprint arXiv:1712.05438, 2017
902017
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